Method of grouping users to reduce interference in mimo-based wireless network

ABSTRACT

In a system of MIMO communications in a wireless network, a number of wireless units are logically divided into a plurality of user groups, through operation of a semi-orthogonal user selection sub-system. For example, the user selection sub-system may implement a heuristic user selection algorithm based on near-orthogonality. Each user group is assigned a discrete transmission channel, which may be orthogonally defined in terms of frequency, time, or code. Data is transmitted over the channels (e.g., from network base stations) in a coherently coordinated manner, according to a zero-forcing beamforming operation. The system may be configured for operation in a time/frequency selective manner, e.g., over time/frequency selective fading channels. The wireless units may be allocated to the time/frequency slots based on prioritization of channel strength and considerations of fairness, in conjunction with the application of a semi-orthogonal user selection algorithm.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.11/796,328 filed on Apr. 27, 2007, and incorporates by reference subjectmatter disclosed in that application in its entirety.

FIELD OF THE INVENTION

The present invention relates to communication systems and, moreparticularly, to methods of radio frequency communications in a wirelessnetwork.

BACKGROUND OF THE INVENTION

Wireless, radio frequency (RF) communication systems enable people tocommunicate with one another over long distances without having toaccess landline-connected devices such as conventional telephones. In atypical cellular telecommunications network (e.g., mobile phonenetwork), an area of land covered by the network is geographicallydivided into a number of cells or sectors, which are typicallycontiguous and which together define the coverage area of the network.Each cell is served by a base station, which includes one or morefixed/stationary transceivers and antennae for wireless communicationswith a set of distributed wireless units (e.g., mobile phones) thatprovide service to the network's users. The base stations are in turnconnected (either wirelessly or through land lines) to a mobileswitching center (“MSC”) and/or radio network controller (“RNC”), whichserve a particular number of base stations depending on network capacityand configuration. The MSC and RNC act as the interface between thewireless/radio end of the network and a public switched telephonenetwork or other network(s) such as the Internet, including performingthe signaling functions necessary to establish calls or other datatransfer to and from the wireless units.

Various methods exist for conducting wireless communications between thebase stations and wireless units. Examples include CDMA (code divisionmultiple access), TDMA (time division multiple access), and OFDM(orthogonal frequency-division multiplexing). CDMA, widely implementedin wireless networks in the United States, is a spread-spectrummultiplexing scheme wherein transmissions from wireless units to basestations are across a single frequency bandwidth known as the reverselink. Generally, each wireless unit is allocated the entire bandwidthall of the time, with the signals from individual wireless units beingdifferentiated from one another using an encoding scheme. Transmissionsfrom base stations to wireless units are across a similar frequencybandwidth known as the forward link. In TDMA-based systems, which arewidely used in Europe and elsewhere, frequency channels are divided intotime slots for sharing among a plurality of users, e.g., the informationfor each user occupies a separate time slot of the frequency channel. InOFDM, the available RF bandwidth is divided into several sub-channels.The bit stream to be transmitted is split into a plurality of parallel,low-rate bit streams. Each bit stream is transmitted over one of thesub-channels by modulating a sub-carrier using a standard modulationscheme. The sub-carrier frequencies are chosen so that the modulateddata streams are orthogonal to one other, meaning that interferencebetween the sub-channels is eliminated.

Many wireless networks have a government-assigned frequency spectrum forsupporting communications between the end users' wireless units and thenetwork's base stations. Because of this limited bandwidth, and becausethe demand on this bandwidth increases as the number of wireless usersincreases, it is desirable in a wireless system to use the availablefrequency spectrum in an efficient manner. In particular, given a setbandwidth, greater efficiency generally corresponds to an increasednumber of users and/or data throughput.

To better utilize the frequency spectrum in a wireless network, serviceproviders have begun to implement multiple-input multiple-output(“MIMO”)-based RF transmission systems. In MIMO systems, the transmitter(e.g., base station) is provided with multiple antennas capable oftransmitting spatially independent signals, while the receiver (e.g.,wireless unit) is equipped with multiple receive antennas. “MIMO” alsoencompasses systems where transmissions from a number of base stationsor other transmitters are coordinated for mitigating against inter-cellinterference. In both cases, by using a sophisticated signal-processingscheme to control transmissions it is possible to achieve significantincreases in throughput and range without an increase in bandwidth oroverall transmit power expenditure. In general, MIMO technologyincreases the spectral efficiency (e.g., measured as the number ofinformation bits transmittable per second of time and per hertz ofbandwidth) of a wireless communication system by exploiting the spacedomain, because the multiple transmission sources are physicallyseparated in space.

MIMO systems have the potential to achieve high throughputs in wirelesssystems. When channel state information (CSI) is available at thetransmitter, the base station can transmit to multiple userssimultaneously to achieve a higher rate. For efficiently transmittingdata to multiple users at the same time, the “dirty paper coding” (DPC)transmission technique has been shown to achieve the sum-rate capacity(i.e., maximum throughput) of the multiple-antenna broadcast channel.DPC is a signal processing and pre-coding scheme that allows atransmitter to send information to multiple users so that many of theusers see no interference from other users, in a lossless manner (e.g.,without incurring any power increase or rate loss). However, DPC isdifficult to implement in practical systems due to the highcomputational burden of successive encodings and decodings, especiallywhen the number of users is large.

SUMMARY OF THE INVENTION

An embodiment of the present invention relates to a method and system ofMIMO communications in a wireless network, for grouping users to reduceinterference. The network includes a plurality of spatially distributedtransmission sources (e.g., a base station with multiple spaced-aparttransmit antennas, and/or multiple base stations) and a plurality ofwireless units. (By “wireless unit” or “user,” it is meant mobilephones, wireless PDA's, computerized vehicle navigation systems,wireless devices with high-speed data transfer capabilities, such asthose compliant with “3-G” or “4-G” standards, “WiFi”-equipped computerterminals, or the like.) In operation, the wireless units are logicallydivided into a plurality of user groups, through application of asemi-orthogonal user selection algorithm, e.g., a heuristic userselection algorithm based on near-orthogonality. Each user group isassigned a discrete transmission channel. (The transmission channels canhave equal bandwidths, and together typically occupy the total bandwidthdesignated for transmissions to the wireless units. The channels may bedefined in terms of frequency, time, and/or code.) Over the assignedtransmission channels, data is transmitted from the transmission sourcesto the user groups in a coherently coordinated manner, according to azero-forcing beamforming (ZFBF) operation. (For example, a separate ZFBFprecoder may be applied to each transmission channel.) Typically, adesignated transmission power constraint is applied to the transmissionsources, by which it is meant that the sum transmission power and/or thetransmission power at each source are maintained within certainboundaries.

By combining ZFBF with semi-orthogonal user selection forgrouping/allocating users to transmission channels, it is possible forthe MIMO communication system to achieve asymptotically optimalperformance at the limit of a large number of wireless units (i.e.,performance is optimal when communicating with a large number of users).Such a system has performance levels approaching those using dirty papercoding, but is much more easily implemented in terms of signalprocessing and the like. System performance is robust over a widesignal-to-noise ratio range, and improves as the number of usersincreases and/or as the number of transmission sources decreases.

In another embodiment, the semi-orthogonal user selection processresults in a certain percentage of the active wireless units in thewireless network being blocked. Thus, according to the user selectionprocess, some of the wireless units are formed into user groups forcoherently coordinated, ZFBF-based transmissions. The remaining wirelessunits are not assigned to groups, thereby in effect being blocked fromreceiving transmissions.

In another embodiment, the MIMO communication system operates in atime/frequency selective manner, e.g., over time/frequency selectivefading channels. After optionally blocking a portion of active wirelessunits based on path loss and shadow, the remaining wireless units areallocated or assigned to a plurality of transmission channels, e.g., aplurality of time/frequency slots that divide the bandwidth apportionedfor downlink transmissions to the wireless units. (In effect, groups ofwireless units are formed, each of which is assigned a time/frequencyslot. Thus, out of “K” total wireless units, “M” of the wireless unitsare allocated to each time/frequency slot, where M<<K.) The wirelessunits may be allocated to the time/frequency slots based onprioritization of channel strength and considerations of fairness, inconjunction with the application of a semi-orthogonal user selectionalgorithm. Subsequent to user allocation/grouping, signals aretransmitted to the users over the transmission channels at a minimumguaranteed rate, according to ZFBF operations and a transmission powerallocation. Transmission power is allocated according to aper-transmission antenna power constraint or a sum over antennas powerconstraint.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be better understood from reading thefollowing description of non-limiting embodiments, with reference to theattached drawings, wherein below:

FIG. 1 is a schematic diagram of MIMO-based communications in a wirelessnetwork;

FIG. 2 is a schematic diagram of a MIMO communication system accordingto an embodiment of the present invention;

FIG. 3 is a schematic diagram showing a user grouping process accordingto an embodiment of the present invention;

FIG. 4 is a simplified flow chart showing a method of semi-orthogonaluser selection/grouping;

FIG. 5 is a flow chart showing the method of semi-orthogonal userselection/grouping in more detail;

FIG. 6 is a convex optimization problem for optimizing bandwidth andpower allocations amongst users;

FIG. 7 is a flow chart illustrating operation of an additionalembodiment of the MIMO communication system;

FIG. 8 illustrates the allocation or grouping of wireless units/usersinto time/frequency slots;

FIGS. 9-10B illustrate several different user allocation algorithms;

FIG. 11 is a convex optimization problem for a per-transmission sourcepower constraint;

FIGS. 12A-12C illustrate a convex optimization problem for a sum powerconstraint; and

FIG. 13 is a table showing a rate update process.

DETAILED DESCRIPTION

Turning to FIGS. 1-13, the present invention relates to a method andsystem 10 of MIMO communications in a wireless network 11. The network11 includes a plurality of spatially distributed transmission sources 12(e.g., a base station (“BS”) 14 a with multiple spaced-apart transmitantennas 16, and/or multiple base stations 14 a-14 f) and a plurality ofwireless units 20 a-20 e. (By “wireless unit,” it is meant a mobilephone, wireless PDA, computerized vehicle navigation system, wirelessdevices with high-speed data transfer capabilities, such as thosecompliant with “3-G” or “4-G” standards, “WiFi”-equipped computerterminals, or the like.) In operation, the wireless units 20 a-20 e arelogically divided into a plurality of user groups 22 a-22 c, throughoperation of a semi-orthogonal user selection or grouping sub-system 24.For example, the user selection sub-system 24 may implement a heuristicuser selection algorithm based on near-orthogonality. Each user group 22a-22 c is assigned a discrete transmission channel 26 a-26 c.(Typically, the transmission channels have equal bandwidths “ W”, andtogether occupy the total bandwidth 28 designated for transmissions tothe wireless units in the network 11. The channels may be orthogonallydefined in terms of frequency, time, or code.) Over the assignedtransmission channels 26 a-26 c, data 30 is transmitted from thetransmission sources 12 to the wireless units in the user groups 22 a-22c in a coherently coordinated manner, according to a zero-forcingbeamforming (ZFBF) operation. (For example, a separate ZFBF precoder 32a-32 c may be applied to each transmission channel.) Typically, adesignated transmission power constraint is applied to the transmissionsources, by which it is meant that the sum transmission power and/or thetransmission power at each source are maintained within certainboundaries.

Because end users (e.g., network subscribers) utilize and control thewireless units, the terms “user” and “wireless unit” are usedinterchangeably in the present description. Thus, for example,references to “user groups” and the like relate to groupings of wirelessunits, as opposed to groupings of end users independent of the wirelessunits.

The system 10 may be implemented in conjunction with any type ofwireless network 11, including wide area cellular, ad hoc, WiMax, andWiFi networks. Operation of the system 10 is described herein primarilywith respect to a cellular telecommunications network. However, this isfor illustration purposes only, and the system may be adapted for use inother types of wireless networks.

In the case of a cellular network, as noted above, the network 11 isgeographically divided into a number of cells or sectors 34, which arecontiguous and which together define the coverage area of the network11. Each cell 34 is served by a base station 14 a-14 f, which includesone or more transmission sources 12 (e.g., fixed/stationary transceiversand antennae) for wireless communications with the wireless units 20a-20 e. The base stations 14 a-14 f are in turn connected to a mobileswitching center (“MSC”), radio network controller (“RNC”), or otherupstream network entity 36.

As indicated above, the system 10 implements a method of MIMOcommunications, wherein RF transmissions from a plurality ofspaced-apart transmission sources 12 to a plurality of wireless units 20a-20 e are coherently coordinated based on zero-forcing beamforming andsemi-orthogonally selected user groups. Coordinating transmissions inthis manner reduces inter-cell interference, thereby increasing networkcapacity. FIG. 1 shows a first example of MIMO communications generally,with a number of base stations 14 a-14 f transmitting signals to awireless unit “k” 20 a. The wireless unit 20 a is one of “K” totalactive wireless units in the network. (“Active” wireless unit refers towireless units that are admitted to the network, and that requirededicated power/bandwidth resources. Those units that are within networkrange and powered up but are “silent” should be considered as inactiveunits.)

FIG. 2 shows a more generalized view of the system 10, where a number oftransmission sources 12 transmit signals to a number of wireless units20 a-20 e. (This is applicable to the case of a single base station withmultiple transmission sources, as well as for multiple base stationseach with one or more transmission sources.) More specifically, thesystem 10 is generally modeled as having “M” transmit antennas or othertransmission sources 12 and K randomly placed wireless units 20 a-20 e.The kth user channel (i.e., logical channel for data transmissions tothe user) is denoted as:

h _(k) =|h _(k) |{tilde over (h)} _(k),

where |h_(k)| is the magnitude of the channel vector drawn from a knowndistribution g( ) and {tilde over (h)}_(k) is a unit vector thatrepresents the channel direction, independent of h_(k) and uniformlydistributed over the unit norm sphere in the M-dimensional complexEuclidian space C^(1×m). ({tilde over (h)}_(k) being uniformlydistributed is true only for the case of a single base station. It isnot true for multiple base stations.) Thus, {tilde over (h)}_(k) modelsa random phase due to a Rayleigh fading, and g( ) captures the channelgain that includes, for example, the effect of a path loss, shadowfading, and Rayleigh fading.

Without loss of generality, users are sorted in decreasing order oftheir channel norms 38:

|h _(i) |, e.g., |h ₁ |> . . . >|h _(k)|.

“Channel norm” 38 (see FIG. 3) refers to a measure of the quality of thecurrent channel realization. Channel norms 38 are often obtained usingfast feedback of an estimated instantaneoussignal-to-interference-and-noise ratio (SNR), e.g., as estimated frombroadcasted pilot signals received at the wireless units. A userblocking probability of P_(b) is allowed, wherein the system may ineffect “discard” up to └KP_(b)┘ users as part of the semi-orthogonaluser selection/grouping process. (In other words, subsequent toapplication of the semi-orthogonal user selection/grouping process, upto └KP_(b)┘ users may remain unassigned to any users groups, therebybeing blocked or discarded.) The semi-orthogonal user selectionalgorithm chooses users based on both near-orthogonality and channelnorms 38. When the number of users K is very large, it is asymptoticallythe case that users that belong to the worst └KP_(b)┘ (in terms ofchannel norms) have a high chance of being blocked, and users thatbelong to the best ┌K (1−P_(b))┐ have a high chance of being assigned tothe transmission channels 26 a-26 c. Therefore, ┌K (1−P_(b))┐ users areasymptotically chosen as a result of the application of thesemi-orthogonal user selection algorithm. In thetime-frequency-selective version of the user allocation algorithmdiscussed below, it is possible to discard └KP_(b)┘ users in advancebased on their average channel norm, but this is an optional feature.

For the users chosen as a result of the application of thesemi-orthogonal user selection algorithm (e.g., up to ┌K (1−P_(b))┐users, asymptotically), the system 10 is optionally configured todeliver an equal minimum rate “R”, i.e., for fairness, each user isguaranteed at least a minimum transmission rate R. Under theseconditions, the objective is to maximize the common rate R under theZFBF constraint. Of particular interest is the asymptotic case of thenumber of users K growing to infinity while M (the number oftransmission sources) is fixed. To maintain a non-vanishing R as Kincreases, a proportionate growth of the total bandwidth “W” 28 isallowed as follows

W=η(1−P _(b)) W,

where η=K/M>>1 is a user loading factor. The sum transmit power “P”(i.e., the system-wide transmit power) also grows linearly with K, andis constrained as follows:

P≦K(1−P _(b)) P,

where P refers to the average power available to each user. Since atmost M<<K users can be simultaneously supported using ZFBF, the totalbandwidth 28 is divided into “D” sub-channels 26 a-26 e, each having anequal bandwidth W, after which a separate ZFBF precoder 32 a-32 c isapplied to each sub-channel. The system 10 may also include asub-channel multiplexer 37, as shown in FIG. 2.

As noted, users may be guaranteed at least a minimum transmission rateunder certain embodiments of the present invention. This is applicablenot only to providing guaranteed minimum transmission rates to all usersin a particular group, but also to providing different guaranteedminimum transmission rates to different groups, or to differentsub-groups within a group, or the like. For example, if the network hasseveral different types or classes of wireless units, it is possible toprovide equal rates for all wireless units within a class, but to havedifferent equal rates from class to class. It also possible for thesystem to be configured in other manners as relating to transmissionrates, e.g., equal minimum rates are not guaranteed, or only certainusers or classes of users are guaranteed an equal minimum rate.

ZFBF operations are characterized as indicated in FIG. 2. The set ofusers assigned to the “i th” sub-channel 26 a-26 c is denoted as S_(i)⊂{1, . . . , K}, i=1, . . . , D. (The process for assigning orallocating users to sub-channels is discussed in more detail below.) Theset of blocked users 40 is denoted as S₀ ⊂{1, . . . , K}. Then, S₀, . .. , S_(D) partition {1, . . . , K} and satisfy |S_(o)|≦└KP_(d)┘,|S_(i)|≦M, for i=1, . . . , D. Let y_(k) and z_(k) be the receivedsignal and the additive noise, respectively, at user k. The stackedchannel matrix for the users in S_(i) is denoted as H_(Si)εC^(|Si|×M),i.e., the rows of H_(Si) are channels of the users in S_(i). Thereceived signal vector y_(Si)εC^(|Si|×1) and the noise vectorz_(Si)εC^(|Si|×m) are defined in a similar manner. The transmit symbolvector for S_(i) is denoted as x_(Si). Thus:

y _(Si) =H _(Si) ×z _(Si)

In ZFBF with a common rate support, the vector x_(Si) is given byx_(Si)=(√γ)W_(Si)s_(Si) where γ is the target received signal power,W_(Si)=H*_(Si)(H_(Si)H*_(Si))⁻¹, the pseudo-inverse of H_(Si), ands_(Si) is the information symbol vector for the users with a normalizedpower E(|s_(Si)|²)=1. This gives the following:

y _(Si)=(√γ)s _(Si) +z _(Si), or y _(k)=(√γ)s _(k) +z _(k) for ∀kεSi.

Thus, every non-blocked user achieves the same rate:

R=(W/D) log₂(1+(γ/(N ₀ W/D))),

where N₀ is the noise power spectral density at each user. The targetreceived power γ is determined by the power constraint P.

As noted above, prior to ZFBF operations, the user selection sub-system24 divides up to ┌K (1−P_(b))┐ of the wireless units 20 b-20 e into aplurality of user groups 22 a-22 c, each of which is assigned a discretetransmission sub-channel 26 a-26 c. In one embodiment, for example, theuser selection sub-system 24 implements a heuristic userselection/grouping algorithm based on near-orthogonality. By groupingusers semi-orthogonally in combination with ZFBF, the commontransmission rate R of the system 10 approaches its theoreticalinterference-free upper bound as the number of users K grows large.

For semi-orthogonal grouping, the users 20 a-20 e are grouped into anumber of channels 26 a-26 c, each of which includes at most M users,where M<<K. This is done according to a heuristic and greedy userselection algorithm based on near-orthogonality, as shown in simplifiedform in FIG. 4. The process starts at Step 100, for forming the firstuser group 22 a. At Step 102, the user grouping sub-system 24 selectsthe user with the largest channel norm 38. This user is added to theuser group at Step 104. If M users have been chosen for the group, asdetermined at Step 106, or if there are no more candidate users forpossible inclusion in the current group, the current group is consideredcomplete and the process continues at Step 100 for forming the nextgroup. If └KP_(b)┘ users remain, as determined at Step 108, the processends. Otherwise, at Step 110, the sub-system eliminates the remainingusers that are not near-orthogonal to the selected user. (“Eliminate”means that the user is withdrawn as a potential candidate for thecurrent group; eliminated users may eventually be assigned to othergroups, or blocked for transmissions if they have low channel norms orotherwise.) Of the remaining users, all of which are near-orthogonal tothe selected user, the sub-system 24 selects the user with the largestchannel norm 38, as at Step 102. This user is added to the firstselected user in the user group, as at Step 104, and the processcontinues as described above until the group is complete or until└KP_(b)┘ users are left. For the next and subsequent groups, thisprocess is repeated for users that have not yet been assigned to groups,until no more than └KP_(b)┘ users remain. As noted above, when thenumber of users K is very large, it is asymptotically the case thatusers that belong to the worst └KP_(b)┘ have a high chance of beingblocked.

The user grouping process is based on a semi-orthogonal user selectionalgorithm, in particular, a greedy user selection or greedy weightedclique algorithm. (Semi-orthogonal user selection algorithm, greedy userselection algorithm, and the weighted clique algorithm refer generallyto the same thing. All the semi-orthogonal user selection algorithmshave a greedy nature in the sense that they try to select the best userat each iteration.) A greedy user selection algorithm is advantageousfor its simplicity. However, other semi-orthogonal user selectionalgorithms could be used instead. According to the semi-orthogonal userselection algorithm, a group of users S_(i), |S_(i)|≦M is selected suchthat the selected users are near orthogonal within ε, e.g., |{tilde over(h)}_(k){tilde over (h)}_(l)*|<ε, ∀k, jεS_(i), k≠j. The algorithm alsoattempts to maximize the users' channel magnitudes by choosing, for eachiteration, the user with the largest channel magnitude amongst usersthat satisfy the near-orthogonality constraint. The users selected froma single run of the semi-orthogonal user selection algorithm areassigned a transmission sub-channel 26 a-26 c. The semi-orthogonal userselection algorithm is repeatedly applied to the remaining users untilno more than └KP_(b)┘ users remain unassigned.

This process is shown in more detail in FIG. 5. At Step 120, a currentsub-channel index i is set to i=1. S={1, . . . , K} is the set ofremaining users. At Step 122, a first iteration of the semi-orthogonaluser selection algorithm is carried out for forming a first user group.Step 124 indicates that: T₁=S is the candidate user set for the i thsub-channel (i.e., the candidate users for possible inclusion in the ith sub-channel are those left in the set of remaining users 5); j=1 is acurrent user index; and S_(i)=ø (empty set) for the i th group of users(i.e., the current group of users is initially empty). At Step 126, theuser with the largest channel norm is selected, as indicated. At Step128, the selected user is added to the current group. At Step 130, usersthat are not near-orthogonal to the selected user are eliminated forpossible inclusion in the current group. At Step 132, it is determinedif the current group S_(i) has fewer than M members, and if there arestill candidate members available for possible inclusion in the currentgroup. If so, the user index is incremented at Step 134, and the processcontinues at Step 126 for adding more users to the group. If not, the ith sub-channel/user grouping is considered complete, as at Step 136. AtStep 138, the users added to the i th sub-channel are removed from theset of remaining users S. At Step 140, it is determined if there aremore than └KP_(d)┘ users left. If so, the process continues forassigning users to the next sub-channel, as at Step 142, through anotheriteration of the semi-orthogonal user grouping algorithm at Step 122 etseq. If not, the process ends at Step 144, with up to └KP_(d)┘ remainingusers being blocked for transmissions. The semi-orthogonal user groupingprocedure is asymptotically optimal, efficiently eliminatingmulti-stream interference among the group of users in the samesub-channel.

After the user grouping process is completed, the total bandwidth 28,e.g., W=η(1−P_(b)) W, is divided into D equal-bandwidth sub-channels,where D=i as indicated in FIG. 5. In other words, for as many usergroups 22 a-22 c are formed, the available bandwidth is divided intothat many sub-channels 26 a-26 c. The users in S_(i) are then assignedto the i th sub-channel and are supported using ZFBF as explained above.

The system 10 is based on an equal bandwidth ZFBF scheme. The rate (andthe upper bound) could be further improved by using a flexible bandwidthallocation, which does not yield a closed form expression but requiresjoint optimization of bandwidths and powers. For example, theinterference free upper bound can be further improved by solving theconvex optimization problem 42 shown in FIG. 6, for the optimalbandwidth and power allocations amongst users. W_(k) is the bandwidthallocation for the user k. ZFBF can also be improved in a similarmanner.

As should be appreciated, where the system 10 is characterized herein asinvolving the formation of user groups and then assigning sub-channelsto the groups, these steps are typically carried out simultaneously byassigning selected users to sub-channels, according to a semi-orthogonaluser selection algorithm, in a manner as described above. The users ineach sub-channel constitute a de facto user group or grouping.

Turning now to FIGS. 7-12C, an additional embodiment of the MIMOcommunication system 50 is applicable to multi-cell transmissions overtime/frequency selective fading channels. Signal-fading phenomena candrastically affect the performance of a terrestrial communicationssystem. Often caused by multi-path conditions, fading can degrade thebit-error-rate (BER) performance of a digital communications system,resulting in lost data or dropped calls. Frequency selective fading is aradio propagation anomaly caused by partial cancellation of a radiosignal by itself—the signal arrives at the receiver by multiple paths,and at least one of the paths is changing (e.g., lengthening orshortening). This causes different frequencies of the received signal tobe attenuated and phase shifted differently in the transmission channel.The system 50 takes advantage of frequency selective fading, becauseusers are chosen with “highest priority” for each channel.

The system 50 is configured to carry out a method of MIMO communicationsin a time/frequency selective manner. The system includes a designateddownlink/forward link bandwidth 28, which is logically divided into anumber of MIMO downlink channels 52 as discussed below. Thecommunication network is similar to as shown in FIG. 1, and includes “M”transmission sources (e.g., M cells each with a single antenna basestation) and “K” single-antenna wireless units or users randomly placedin the network. Signals transmitted from the base stations to the usersare considered to experience path loss (i.e., signal attenuation), withindependent log-normal shadowing and Rayleigh fading for each user.Rayleigh fading is independent over time/frequency. (As should beappreciated, log-normal shadowing, Rayleigh fading, etc. aremathematical models of the distortion that a carrier-modulatedtelecommunication signal experiences over certain propagation media, andas such are only approximations or idealizations of real RF signalpropagation characteristics.) The system 50 may be configured to delivera common minimum rate “R” to each user using ZFBF over the transmissionchannels 52. The transmission apparatus of the system 50 is configuredsimilarly to that shown in FIG. 2.

FIG. 7 summarizes operation of the MIMO communication system 50. At Step200, active users are allocated or assigned to the transmission channels52. In effect, groups of wireless units are formed, each of which isassigned a time/frequency slot. Thus, out of K total wireless units, Mor fewer of the wireless units are allocated to each time/frequencyslot, where M<<K. Subsequent to user allocation at Step 200, signals aretransmitted to the users according to the channel allocations, usingZFBF at Step 204 and a power allocation at each base station or othertransmission source, as at Step 206.

As indicated at 202, as an optional feature, a portion of the activeusers may be blocked based on path loss and shadow. In other words, acertain percentage of users (e.g., └KP_(d)┘ users) will experience poorchannel conditions due to path loss and shadow, and these users aretemporarily blocked for transmissions by being excluded from assignmentto the transmission channels. In the case of the blocked users discussedabove, the blocking results from the user selection process, e.g.,certain users may not be assigned to groups, and, therefore, are ineffect blocked. Here, prior to assignment, the system discards up to└KPb┘ users, based on having the poorest channel norms among thewireless units 20 a-20 e, or upon other, similar criteria.

As shown in FIG. 8, the designated transmission time/frequency bandwidth28 (TW) is divided into “T” transmission channels 52, each of which is atime/frequency slot 54. Thus, in the case of T=200, for example, therecould be 200 time slots in a flat fading time varying channel, 200frequency slots in a frequency selective static channel, or 20 timeslots, each divided into 10 frequency slots, in a time/frequencyselective channel. As indicated, the users are allocated to thetime/frequency slots 54 in a manner wherein each user is eitherscheduled in a particular slot or not. Transmission power is allocatedin each time/frequency slot, such that each user is guaranteed theminimum rate R and the transmission power at each transmission source isconstrained as TP.

The user allocation process 200 can be carried out according to one ofseveral different heuristic algorithms. For example, it would bepossible to choose M users at random for allocating to eachtime/frequency slot 54. It would also be possible to choose M users foreach time/frequency slot 54 according to those having the highestchannel strengths. With reference to FIG. 9, for example, users could beprioritized as indicated in Step 208 (the indicated equation is theratio of the user's instantaneous channel strength to its averagechannel strength), and the M users with the highest priority would bechosen at Step 210. Still further, users could be prioritized asindicated in FIG. 9, with the subsequent application of asemi-orthogonal user selection algorithm to choose one user group,similarly to the manner described above with respect to FIG. 5. (Forexample, at Step 126, the user with the highest priority would beselected and grouped with near-orthogonal users until M users wereselected for the time/frequency slot allocation.)

Alternatively, for improved results, users could be allocated to eachtime/frequency slot 54 according to considerations of fairness, forexample, as shown in FIGS. 10A and 10B. In FIG. 10A, users are assignedto time/frequency slots 54 based on priority of channel conditions andfairness. For each time/frequency slot, at Step 212, users areprioritized as indicated, for promoting fairness, wheref_(k)(t)=2̂{—expected cumulative rate of user k through channels 1 to t+mean of expected cumulative rates of all users through channels 1 to t}.Those users with higher cumulative rate have a smaller f_(k)(t), andthus their priorities are reduced by the amount by which theircumulative rate exceeds the league average among all users. This has asimilar role as the rate discount factor used in the proportional fairscheduling process. At Step 214, the M users with the highest priorityare chosen for allocation to the time/frequency slot in question. InFIG. 10B, users are allocated according to prioritization, fairness, anda semi-orthogonal selection. Thus, users are prioritized as at Step 212,but at Step 216, a semi-orthogonal user selection algorithm is appliedto choose one user group for allocation to the time/frequency slot inquestion. Based on numerical analysis, best results may be achievedusing the method summarized in FIG. 10B.

Power allocation, as at Step 206 in FIG. 7, can be based on aper-transmission source power constraint or a sum power constraint. Theformer may be defined as a convex optimization problem 56, e.g., asshown in FIG. 11, which can be solved using standard convex optimizationtechniques. (It is possible to use other optimization procedures. Assuch, the convex optimization technique(s) described herein are merelyexemplary.) Power allocation based on a sum power constraint is also aconvex optimization problem 58, as shown in FIG. 12A, which is feasibleif P*_(min)≦ PMTP. A Lagrangian 60 for this is as shown in FIG. 12B.Setting ∂L/∂P=0 and ∂L/∂P_(kt)=0 results in equations 62 and 64 as shownin FIG. 12C. Here, λ is a Lagrange multiplier associated with thepositively of individual power constraints. v is a Lagrange multiplierassociated with the sum power constraint. Finally, ω is a Lagrangemultiplier associated with the rate requirement. In operation, R isupdated, followed by determinations of {ω_(k)} and {P_(kt)}.Subsequently, the power constraint P_(kt) is checked, and the processcontinues by again updating R. For a given R, the Lagrange multipliers wfor each k are obtained from equation 64. Then, P_(kt) and P_(min) areobtained from equation 62 and equation 66, respectively. If the obtainedP_(min) is feasible, then the rate R can be increased. If P_(min) isinfeasible, the rate R is decreased. The update on R can be done, forexample, by using bisection as in the table in FIG. 13.

The methods, processes, and/or algorithms described herein may beimplemented using electronic hardware, software (e.g., scripts, softwareprograms, suites of software programs), or a combination of the two,using standard programming, signal processing, and/or electrical designmethods. Backhaul communication links are required. The implementationalso requires that hardware and software accommodate the measuring andtransmission of channel state information for each base antenna to userantenna link. The timely availability of channel state information isrequired for carrying out the network coordination algorithms.

Although the method and system have been primarily illustrated asinvolving semi-orthogonal groupings of users within a frequency band,other means can be used to group users, based on different orthogonalways of nominally disjoint partitioning of communication resources. Forexample, it would be possible to group a plurality of terminals using(i.e., within) a CDMA code, in place of grouping within a frequencyband. Doubling the number of orthogonal dimensions to partition, usingtwo states of polarization instead of one, is also possible.

Since certain changes may be made in the above-described system of MIMOcommunications in a wireless network, for grouping users to reduceinterference, without departing from the spirit and scope of theinvention herein involved, it is intended that all of the subject matterof the above description or shown in the accompanying drawings shall beinterpreted merely as examples illustrating the inventive concept hereinand shall not be construed as limiting the invention.

We claim:
 1. A method of MIMO communications for use in a wirelessnetwork including at least a first base station and a second basestation, said method comprising: semi-orthogonally selecting a pluralityof wireless units in the wireless network for assignment to a pluralityof designated transmission channels; and transmitting data signals tothe plurality of wireless units over the assigned transmission channels,said data signals being transmitted from at least one of the first basestation and the second base station according at least to a zero-forcingbeamforming (ZFBF) operation.
 2. The method of claim 1 wherein the datasignals are transmitted also according to at least one designatedtransmission power constraint of the first and second base stations. 3.The method of claim 2 wherein: each of the first and second basestations has at least one transmit antenna; and the at least onedesignated transmission power constraint comprises at least one of aper-transmit antenna transmission power constraint and a per-basestation transmission power constraint.
 4. The method of claim 2 whereinthe transmission channels are discrete channels having equal bandwidths,and wherein the data signals are transmitted to the first plurality ofwireless units at equal minimum rates.
 5. The method of claim 4 whereinthe semi-orthogonal selection results in a second plurality of wirelessunits being blocked from receiving transmissions, based at least in parton channel norms of the wireless units.
 6. The method of claim 1 whereinthe wireless units are semi-orthogonally selected for assignment to thetransmission channels according to a greedy user selection algorithmthat includes a near-orthogonality assessment of the wireless units. 7.A method of MIMO communications in a wireless network including at leasta first base station and a second base station, said method comprising:forming a plurality of user groups on a semi-orthogonal selection basis,wherein each of the user groups includes a different subset of theplurality of wireless units in the wireless network; and for each of theuser groups, transmitting data signals to the wireless units in the usergroup over a discrete transmission channel assigned to the user group,wherein the data signals are transmitted from at least the first basestation and the second base station based on zero-forcing beamforming(ZFBF) of the data signals.
 8. The method of claim 7 further comprising:blocking transmissions to wireless units not assigned to the usergroups.
 9. The method of claim 7 wherein the transmission channels haveequal bandwidths, and wherein the data signals are transmitted to thewireless units in the user groups at equal minimum rates.
 10. The methodof claim 7 wherein the data signals are transmitted according to atleast one designated transmission power constraint of the first andsecond base stations.
 11. The method of claim 10 wherein: each of thefirst and second base stations has at least one transmit antenna; andthe at least one designated transmission power constraint comprises atleast one of a per-transmit antenna transmission power constraint and aper-base station transmission power constraint.
 12. The method of claim7 wherein the wireless units are semi-orthogonally selected for formingthe user groups according to a greedy user selection algorithm thatincludes a near-orthogonality assessment of the wireless units.
 13. Acommunications system for MIMO communications in a wireless network,comprising: a first base station having one or more transmit antennasfor wireless communications with at least one user group of wirelessunits formed at least in part based on a semi-orthogonal selection of asubset of a plurality of wireless units in the wireless network; whereinat least one of the first base station and a second base station isconfigured to transmit data to the wireless units in said at least oneuser group over an assigned transmission channel according to azero-forcing beamforming (ZFBF) operation and according to at least onedesignated transmission power constraint applied to said at least onebase station, the designated transmission power constraint comprising atleast one of (1) a first transmission power constraint applied on aper-transmission basis for each transmit antenna of said at least onebase station and (2) a second transmission power constraint applied on asum transmission basis for all transmit antennas of said at least onebase station.
 14. The communications system of claim 13, wherein data istransmitted from said at least one base station to a plurality of usergroups, each of the user groups comprising a different subset of saidplurality of wireless units, wherein the wireless units in each usergroup are semi-orthogonally selected from among the plurality ofwireless units; and wherein a discrete transmission channel is assignedto each of the user groups so that data transmitted from said at leastone base station to the wireless units in the user groups aretransmitted over respective assigned transmission channels according toa ZFBF operation and at least one designated transmission powerconstraint applied to said at least one base station.
 15. Thecommunications system of claim 14, wherein the transmission channelshave equal bandwidth, and the data is transmitted to the wireless unitsin the user groups according to at least one equal minimum rate.
 16. Thecommunications system of claim 14, wherein: the user groups comprisewireless units in a first subset of said plurality of wireless units;and the wireless units in a second subset of said plurality of wirelessunits are blocked from receiving transmissions over the network, saidsecond subset comprising all the wireless units in the plurality ofwireless units other than those in the first subset, wherein the firstand second subsets are formed based in part on channel norms of theplurality of wireless units.
 17. The communications system of claim 14,wherein the wireless units in each of the user groups aresemi-orthogonally selected according to a greedy user selectionalgorithm that includes a near-orthogonality assessment of the wirelessunits.
 18. The communications system of claim 13, wherein the at leastone designated transmission power constraint is imposed and met in anoptimization procedure.